NDLI: Rao-Blackwellized particle filter for Markov modulated nonlinear dynamic systems

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Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing (Cat. No.01TH8563)

Rao-Blackwellized particle filter for Markov modulated nonlinear dynamic systems

Content Provider	IEEE Xplore Digital Library
Author	Saha, S. Hendeby, G.
Copyright Year	2014
Description	Author affiliation: Dept. Electr. Eng., Linkoping Univ., Linköping, Sweden (Saha, S.; Hendeby, G.)
Abstract	The Markov modulated (switching) state space is an important model paradigm in statistical signal processing. In this article, we specifically consider Markov modulated nonlinear state-space models and address the online Bayesian inference problem for such models. In particular, we propose a new Rao-Blackwellized particle filter for the inference task which is our main contribution here. A detailed description of the problem and an algorithm is presented.
Starting Page	272
Ending Page	275
File Size	130988
Page Count	4
File Format	PDF
ISBN	9781479949755
DOI	10.1109/SSP.2014.6884628
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-29
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Markov processes Hidden Markov models Switches Nonlinear dynamical systems State-space methods Signal processing Aircraft Jump Markov nonlinear systems Rao-Blackwellized particle filter Markov regime switching switching nonlinear state space
Content Type	Text
Resource Type	Article

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